Tunable neural electrode

ABSTRACT

A device includes a substrate, an electrode, an electrical pad, and a signal line. The signal line is coupled to the substrate and covered by an insulation layer. The signal line is coupled to the electrical pad and the electrode. At least one of the electrode and the signal line includes a diamagnetic material and paramagnetic material, wherein a ratio of the diamagnetic material and the paramagnetic material is selected based on the susceptibility properties of a physiological tissue. The term paramagnetic herein refers to magnetic susceptibility greater than that of the surrounding tissue and diamagnetic refers to magnetic susceptibility lower than that of the tissue.

CLAIM OF PRIORITY

This application claims the benefit of priority of U.S. ProvisionalApplication 62/533,873, filed Jul. 18, 2017, which is hereinincorporated by reference in its entirety.

STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT

This invention was made with government support under MH111413,NS070839, MH106049, EB015894, and NS076408 awarded by NationalInstitutes of Health of DGE-069104 awarded by the National ScienceFoundation. The government has certain rights in the invention.

BACKGROUND

Measurement of neural signals is a topic of interest. This can includemeasuring neural electrical signals with high amplification andmeasurement of dopamine in the brain using voltammetry. Stimulation ofneural cells using invasive electrode(s) is also of strong interest.Deep brain stimulation (DBS) can be used to treat diseases such asParkinson's disease and essential tremor, spinal cord stimulation can beused for pain management, and stimulation of the vagus nerve is beinginvestigated for a wide variety of treatments including hypertension.Stimulation of the peripheral nervous system is also underinvestigation.

Additionally, magnetic resonance (MR)-compatible research tools can beuseful for studying the nervous system using functional MR imaging(fMRI) and other types of neural MRI methods as well as for studyingother organs of human body.

Image artifacts induced by the implanted electrodes can impair amultimodal study and outcomes. Image artifacts around implanted neuralrecording and/or stimulating probes can be associated with localmagnetic field distortions.

Image artifacts compromise the MR-signals originating from locationsnearby the implanted electrode, thus preventing the collection ofco-located electrophysiology and fMRI data and introducing challenges inimaging the electrode position inside the tissue after implantationusing MRI. Such artifacts are also problematic in patients implantedwith stimulation electrodes such as DBS electrodes. Artifacts around theimplanted DBS electrodes prevent collection of fMRI data near theelectrode site, limiting the usefulness of studying the mechanisms ofDBS using fMRI.

SUMMARY

This overview is intended to provide an overview of subject matter ofthe present patent application. It is not intended to provide anexclusive or exhaustive explanation of the invention. The detaileddescription is included to provide further information about the presentpatent application.

Example 1 is a device comprising: a substrate having a planar or curved(e.g. cylindrical) surface; at least one signal line affixed to thesubstrate and covered by an insulation layer, wherein each signal lineis coupled to an electrical pad and/or wire and to an electrode,generally in one to one relation, and at least one electrode or signalline includes a diamagnetic material and paramagnetic material in atuned and particular ratio selected based on a physiological tissuesusceptibility property, wherein the properties of diamagnetic andparamagnetic are values relative to that of the tissue.

In Example 2, the subject matter of Example 1 optionally includeswherein the physiological tissue is a neural tissue.

In Example 3, the subject matter of Example 2 optionally includeswherein the neural tissue is in the central nervous system.

In Example 4, the subject matter of any one or more of Examples 2-3optionally include wherein the neural tissue is in the peripheralnervous system.

In Example 5, the subject matter of any one or more of Examples 1-4optionally include wherein the physiological tissue is a cardiac tissue.

In Example 6, the subject matter of any one or more of Examples 1-5optionally include wherein the physiological tissue is in themusculoskeletal system.

In Example 7, the subject matter of any one or more of Examples 1-6optionally include wherein the physiological tissue is an organ in abroad definition.

In Example 8, the subject matter of any one or more of Examples 1-7optionally include wherein the electrode is a recording electrode.

In Example 9, the subject matter of any one or more of Examples 1-8optionally include wherein the electrode is a stimulating electrode.

In Example 10, the subject matter of any one or more of Examples 1-9optionally include wherein the electrode is a recording and stimulatingelectrode.

In Example 11, the subject matter of any one or more of Examples 1-10optionally include wherein the tuned ratio is a volumetric ratio.

In Example 12, the subject matter of any one or more of Examples 1-11optionally include wherein the tuned ratio is selected based on amagnetic susceptibility of the electrode or of the signal line.

In Example 13, the subject matter of any one or more of Examples 1-12optionally include wherein the ratio is selected to substantially matchthe magnetic susceptibility with that of a physiological tissue.

In Example 14, the subject matter of any one or more of Examples 1-13optionally include wherein the diamagnetic material includes gold.

In Example 15, the subject matter of any one or more of Examples 1-14optionally include wherein the paramagnetic material includes aluminum.

In Example 16, the subject matter of any one or more of Examples 1-15optionally include wherein the electrode or signal line includes layersof diamagnetic material and paramagnetic material.

In Example 17, the subject matter of Example 16 optionally includeswherein a layer has a thickness of between 1 and 1000 nm.

In Example 18, the subject matter of any one or more of Examples 1-17optionally include wherein the electrode or signal line is fabricated bydiffusion or co-deposition of the paramagnetic and diamagneticmaterials.

In Example 19, the subject matter of any one or more of Examples 1-18optionally include wherein the electrode or signal line includesdeposited layers.

In Example 20, the subject matter of Example 19 optionally includeswherein a layer has a thickness of approximately 1-1000 nm.

In Example 21, the subject matter of any one or more of Examples 1-20optionally include wherein the electrode or signal line is fabricated byevaporating and heating.

In Example 22, the subject matter of any one or more of Examples 1-21optionally include wherein the electrode or signal line is fabricated byco-depositing the diamagnetic material and the paramagnetic material.

In Example 23, the subject matter of any one or more of Examples 1-22optionally include wherein the electrode or signal line includes anetwork of randomly oriented conductive nanorods/nanomaterials andmatched susceptibility with that of the tissue.

In Example 24, the subject matter of any one or more of Examples 1-23optionally include wherein the electrode and the signal line arefabricated of the same material.

In Example 25, the subject matter of any one or more of Examples 1-24optionally include wherein the electrode includes a layer of carbonnanotubes at an exposed surface.

In Example 26, the subject matter of Example 25 optionally includeswherein the layer of carbon nanotubes has a thickness of approximately10-200 nm.

In Example 27, the subject matter of any one or more of Examples 1-26optionally include wherein the electrode has a layer of electricallyconductive polymer at an exposed surface.

In Example 28, the subject matter of Example 27 optionally includeswherein the electrically conductive polymer includes PEDOT.

In Example 29, the subject matter of any one or more of Examples 27-28optionally include wherein the electrically conductive polymer is formedby deposition.

In Example 30, the subject matter of any one or more of Examples 1-29optionally include wherein the electrode includes a layer ofbiocompatible conductive material at an exposed surface.

In Example 31, the subject matter of Example 30 optionally includeswherein the layer of biocompatible conductive material includes gold.

Example 32 is a fabrication method comprising: providing a substrate;forming at least one signal line on the substrate; forming at least oneelectrode, each electrode coupled to a signal line generally in a one toone relation; at least one electrode or signal line having diamagneticmaterial and paramagnetic material in a ratio determined by theproperties of the physiological tissue, and selectively applyinginsulation to the signal lines, wherein the properties of diamagneticand paramagnetic are values relative to that of the tissue.

In Example 33, the subject matter of Example 32 optionally includeswherein providing the substrate includes providing a polyimidesubstrate.

In Example 34, the subject matter of any one or more of Examples 32-33optionally include wherein forming at least one electrode or signal lineincludes selecting a volumetric ratio between at least two materials.

In Example 35, the subject matter of Example 34 optionally includeswherein selecting the volumetric ratio includes selecting based on amagnetic susceptibility of the electrode or signal line.

In Example 36, the subject matter of any one or more of Examples 34-35optionally include wherein selecting the volumetric ratio includesselecting to substantially match the magnetic susceptibility with thatof the physiological tissue.

In Example 37, the subject matter of any one or more of Examples 32-36optionally include wherein forming the electrode or signal line includesforming using gold.

In Example 38, the subject matter of any one or more of Examples 32-37optionally include wherein forming the electrode or signal line includesforming using aluminum.

In Example 39, the subject matter of any one or more of Examples 32-38optionally include wherein forming the electrode or signal line includesforming layers of diamagnetic material and paramagnetic material withrespect to a physiological tissue.

In Example 40, the subject matter of Example 39 optionally includeswherein forming a layer includes forming a layer having a thickness ofbetween 1 and 1000 nm.

In Example 41, the subject matter of any one or more of Examples 32-40optionally include wherein forming the electrode or signal line includesfabricating by diffusion.

In Example 42, the subject matter of any one or more of Examples 32-41optionally include wherein forming the electrode or signal line includesdepositing layers.

In Example 43, the subject matter of Example 42 optionally includeswherein depositing a layer includes depositing a layer having athickness of approximately 1-1000 nm.

In Example 44, the subject matter of any one or more of Examples 32-43optionally include wherein forming the electrode or signal line includesevaporating and heating.

In Example 45, the subject matter of any one or more of Examples 32-44optionally include wherein forming the electrode or signal line includesco-depositing the diamagnetic material and the paramagnetic material.

In Example 46, the subject matter of any one or more of Examples 32-45optionally include wherein forming the electrode or signal line includesforming a network of randomly oriented conductivenanorods/nanomaterials.

In Example 47, the subject matter of any one or more of Examples 32-46optionally include wherein forming the electrode and/or forming thesignal line includes using a common fabrication technique.

In Example 48, the subject matter of any one or more of Examples 32-47optionally include wherein forming the electrode includes forming alayer of carbon nanotubes at an exposed electrode surface.

In Example 49, the subject matter of Example 48 optionally includeswherein forming the layer of carbon nanotubes includes forming athickness of approximately 10-200 nm.

In Example 50, the subject matter of any one or more of Examples 32-49optionally include wherein forming the electrode includes forming alayer of electrically conductive polymer at an exposed electrodesurface.

In Example 51, the subject matter of Example 50 optionally includeswherein forming the layer of electrically conductive polymer includesforming a layer of PEDOT.

In Example 52, the subject matter of any one or more of Examples 32-51optionally include wherein forming the electrode includes forming alayer of biocompatible conductive material at an exposed electrodesurface.

In Example 53, the subject matter of Example 52 optionally includeswherein forming the layer of biocompatible conductive material includesforming a gold layer.

In Example 54, the subject matter of any one or more of Examples 1-53optionally include wherein forming a variety of MRI-compatible andbiocompatible electrodes with particular susceptibility which matchesthe tissue susceptibility for neural recording and brain stimulationwith minimal MRI susceptibility artifacts and tissue heating safetyconcern.

In Example 55, the subject matter of Example 54 optionally includeswherein is also applicable for other types of tissues and organs besidethe brain.

BRIEF DESCRIPTION OF THE DRAWINGS

In the drawings, which are not necessarily drawn to scale, like numeralsmay describe similar components in different views. Like numerals havingdifferent letter suffixes may represent different instances of similarcomponents. The drawings illustrate generally, by way of example, butnot by way of limitation, various embodiments discussed in the presentdocument.

FIG. 1 illustrates discretized magnetic scalar potential for a 3×3 gridaround central node 5. The shaded nodes are not used in the centraldifference approximations on node 5. The magnetic scalar potential canbe employed to estimate the susceptibility and magnetic field distortionmaps for various designs of electrodes with surrounding tissues.

FIG. 2 illustrates an example of a neural recording or stimulatingelectrode, in accordance with at least one embodiment.

FIGS. 3A, 3B, 3C, 3D and 3E illustrate section and detail views of anelectrode, in accordance with at least one embodiment.

FIGS. 4A, 4B, 4C, 4D and 4E illustrate section and detail views of anelectrode, in accordance with at least one embodiment.

FIGS. 5A, 5B, 5C, 5D and 5E illustrate section and detail views of anelectrode, in accordance with at least one embodiment.

FIG. 6 is a flowchart illustrating an example method of fabricating anelectrode, in accordance with at least one embodiment.

DETAILED DESCRIPTION

The following abbreviations and symbols are used in this document:

ABBREVIATIONS

-   BOLD Blood-oxygen-level dependent-   CNT Carbon nanotube-   EPI Echo planar imaging-   fMRI Functional magnetic resonance imaging-   FOV Field of view-   FSEMS Fast spin echo multiple slice-   GEMS Gradient echo multiple slice-   LFPs Local field potentials-   MRI Magnetic Resonance Imaging-   PDMS Polydimethylsiloxane-   RMS Root-mean-square-   SEM Scanning electron microscope-   SNR Signal-to-noise ratio-   S Signal strength (unitless)-   TE Echo time-   TR Repetition time

Symbols

-   B Magnetic induction or magnetic flux density (T)-   ΔB_(in) Voxel inhomogeneity (T)-   G_(f) Frequency encoding gradient (G cm⁻¹)-   Magnetic field strength (A m⁻¹)-   T₂ Ideal transverse magnetization relaxation time constant, decay    (ms or s)-   T₂* Imperfect (real) transverse magnetization relaxation time    constant, decay (ms or s)-   γ Gyromagnetic ratio (42.58 MHz T⁻¹ for proton)-   μ₀ Magnetic permeability of free space (4π×10⁻⁷ H m⁻¹)-   μ_(r) Relative permeability (unitless)-   x Magnetic volume susceptibility (unitless)-   ΦMagnetic scalar potential (A)-   M Magnetization (A m⁻¹)-   A Matrix of weights for magnetic scalar potentials of interior nodes-   B Matrix of weights for magnetic scalar potentials of boundary nodes-   I Identity matrix-   K Right side of augmented matrix [AIB] after reduction to reduced    echelon form-   {right arrow over (Φ)} Vector of unknown magnetic scalar potentials    of interior nodes-   {right arrow over (u)} Vector of defined magnetic scalar potentials    at boundary nodes

The present subject matter concerns electrodes or electrode arrays, forexample electrodes for recording of tissue signals or for performingstimulation of tissue. The electrode can be configured for recording,stimulating, or recording and stimulating. In at least one example, thepresent subject matter concerns MRI-compatible electrodes for recordingof brain physiological signals or for performing brain stimulation inanimals and humans. The electrode (or more generally, “electrode array”containing a plurality of electrodes in an array) can be tuned to have amagnetic susceptibility close to that of brain tissue. By matching themagnetic susceptibilities of the electrode array and brain tissue, thecreation of magnetic imaging artifacts can be reduced or eliminated.This will enable simultaneous use of fMRI or of a variety of MRI methodsand acquisition of neural physiological signals at the same spatiallocation in the brain. In addition to recording brain physiologicalsignals during MRI, such MRI-compatible electrodes could be used forneural cell stimulation. Stimulating electrodes that are tuned to havemagnetic susceptibility close to that of the surrounding tissue can beused in DBS, spinal cord stimulation, vagus nerve stimulation, andperipheral nerve stimulation. Normally, the presence of an electrode intissue creates a significant artifact which affects MRI/fMRI data at andnear the location of the electrode. The ability to obtain co-located andsimultaneous fMRI and neural signals can help improve understanding ofbrain function and its treatment. The ability to obtain fMRI andstructural MRI data nearby implanted stimulating electrodes can helpimprove understanding of the mechanisms of neural cell stimulation fortreatment of various neurological diseases. It can also allow accurateimaging and localization of the implanted electrodes for significantlyimproving the accuracy and efficacy of implantation and treatment. Whilethe electrode arrays are discussed with regard to neural tissue, theycan similarly be used with and tuned to other tissues, for example,cardiac tissue, muscular tissue, spinal tissue, or the like.

The tuned magnetic susceptibility of the electrodes (or probes) can heachieved by using a combination of paramagnetic and diamagneticmaterials relative to tissue in the appropriate volume ratios so thatthe resulting electrode material has a tuned magnetic susceptibilitynearly equal to that of brain or other organ tissue. Herein,paramagnetic refers to magnetic susceptibility greater than that of thesurrounding physiological tissue and diamagnetic refers to magneticsusceptibility lower than that of the tissue. The ratio of thediamagnetic material and the paramagnetic material can be selected basedon a physiological susceptibility property of the tissue

The distortion of the magnetic field caused by the difference inmagnetic susceptibilities of tissue and the electrode material can alsobe reduced by reducing the volume of susceptibility-mismatched electrodematerial. Very thin layers of high surface area materials, such ascarbon nanotubes (CNT) or other nanostructured materials, can increasethe conductive surface area of the electrode material in contact withbrain tissue. The signal lines that conduct the neural signal toexternal electrical interfaces and the underlying substrate can be tunedto have magnetic susceptibility equal to that of brain tissue, thus,reducing the image artifacts. While the electrode surface in immediatecontact with brain tissue is very thin, has high surface area and lowvolume and may have less image artifacts even though its magneticsusceptibility is not perfectly matched with brain tissue. Such acombination can provide good neural signal acquisition and highconductivity in signal lines and minimal magnetic imaging artifacts.

An example of the present subject matter can be configured to functionas a conductor and/or electrode-tissue interface in an MRI-compatibleneural recording and/or stimulating probe. An MRI-compatible probe canenable multimodal electrophysiology including functional MRI studieswith reduced image artifacts in very strong magnetic fields, togetherwith neural electrical signal acquisition. An MRI-compatible probe canalso be used to stimulate neural tissue and study the effects ofstimulation across the whole brain using fMRI or other types of MRImethods. MRI-compatible probes with reduced image artifacts can enablefMRI signal acquisition nearby implanted stimulation probes forobserving the mechanisms of stimulation with the aim of improving thetreatment efficacy.

The image artifacts discussed in this document are particularly large inthe case of electrodes with significant volume magnetic susceptibilitydifferences from the surrounding brain tissue, for example withtraditional neural recording and stimulating electrodes made of tungstenor platinum or other types of metals. Further, functional imagingsequences utilizing the blood-oxygen-level dependent (BOLD) contrast areespecially artifact prone due to their echo-planar readout andT2*-weighting that makes them very sensitive to changes in magneticsusceptibility.

Another technical challenge posed by implanted electrodes is the tissueheating problem (a safety concern) during the MRI acquisition owing tothe induced eddy currents near the electrodes. One example of thepresent subject matter includes a solution to overcome the safetyconcern and fabricate an electrode having reduced eddy current andtissue heating caused by radiofrequency (RF) power.

Motivation

Functional magnetic resonance imaging (fMRI) is a powerful research toolfor studying the brain noninvasively and as such can be applied in bothhumans and animal models fMRI can map brain activity over the wholebrain at sub-mm scale with approximately 1 Hz or better temporalresolution. Therefore, fMRI is useful for studying functionalconnectivity at resting state and effective connectivity under a workingstate in the brain in both healthy and diseased states. However, thefMRI signal measures changes in cerebral blood volume, blood flow, andblood oxygenation level within brain vessels, and therefore is not adirect measure of neuronal activity. Consequently, the fMRI signal isbased on the so-called blood-oxygen-level dependent (BOLD) effect. Therelationship between the BOLD effect and underlying neuronal activity isnot fully understood, and a better understanding is desired forimproving interpretation of fMRI data and outcomes.

To study the relationship between fMRI BOLD signals and underlyingneural activity, multi-modal electrophysiology-fMRI studies can be used.Such studies involve the implantation of one or more neural recordingelectrodes to acquire neural electrical signals in the brain. Ideally,the neural recording and fMRI are performed simultaneously andco-located. However, traditional neural recording electrodes causeartifacts in fMRI that either preclude their use in simultaneous studiescompletely, or cause signal cancelation/loss at the electrode locationsuch that co-located fMRI and electrophysiological signal acquisition isprevented. These artifacts are the result of a mismatch between themagnetic susceptibility of the electrode and the surrounding tissue.According to one example, a specially created MRI-compatible neuralelectrode having a magnetic susceptibility tuned and matchedspecifically to the surrounding brain tissue can help to eliminate imageartifacts and enable simultaneous, co-located study of fMRI andelectrophysiological signals. Moreover, the technical advancement willallow the structural MRI or other types of MRI collection with reducedimage artifacts as well as precise imaging of the implanted electrodesin brain.

Additionally, deep brain stimulation (DBS) has achieved great successover the last two decades in treatment of many brain disorders such asParkinson's disease, dystonia, essential tremor, depression, epilepsyand obsessive-compulsive disorder. In DBS, an electrode array isimplanted into a specific targeted nucleus in the deep brain and apulsed current with a particular frequency is delivered to restore brainfunctions. The underlying mechanisms of DBS for treating brain diseasesare not yet well understood. There is now growing interest in using MRIfor monitoring and improving DBS treatment efficacy and for basicresearch of understanding brain function changes associated with DBS.MRI is a non-invasive neuroimaging tool, and it can provide excellentimaging contrasts for differentiating abnormal brain tissues withminimal side effects. It can be also used to map functional brainactivities that will help understand the mechanism and response of DBS.However, implanted DBS electrical devices from current commerciallyavailable products (or prototypes from research sites) which usemetallic materials face a daunting challenge owing severe imageartifacts in MRI due to a large susceptibility difference between theelectrode material and brain tissue and tissue heating (safety concern)caused by the RF power and induced eddy current near the electrodeduring the MRI acquisition. These hinder MRI applications in DBSpatients, in particular in high/ultrahigh magnetic field MRI scanners.

By using a specially created electrode material for neural recordingsthat has a magnetic susceptibility tuned to match that of brain tissue,it is possible to eliminate or reduce magnetic image artifacts and toobtain spatially co-located fMRI images at neural electrodes; map theDBS electrodes, identify and optimize the electrode location, and testthe brain responses to the DBS, furthering understanding of themechanisms of DBS. Additionally, a specially tuned recording andstimulating electrode can stimulate neural tissue and record neuralphysiological activity during fMRI. Such technology can provide globalbrain fMRI and network information including co-located measurement withthe electrode and localized neural electrophysiology data in response toDBS stimulation, which can be useful for studying the underlyingmechanisms of DBS and improving the treatment efficacy.

Furthermore, neurons have been shown in vitro to have a high affinityfor nanostructured materials such as carbon nanotubes (CNTs), reducingthe likelihood of a negative immune response and the challengesassociated with it. Neural cells adhere well to carbon nanotubes andgrow preferentially on their surface. CNTS also have high surface areawhich promotes good neural signal acquisition with high signal-to-noiseratio, even with very thin CNT films which has sub-micron thickness. CNTfilms also have the potential to eliminate eddy currents, and thus thesafety concern of tissue heating.

While carbon nanotubes may not have a magnetic susceptibility very wellmatched to that of brain tissue, a very thin CNT film is adequate forneural recordings. It is possible to reduce the volume of CNT used forneural recordings by having an underlying substrate that is very wellmatched with brain tissue and has high thickness (for improvingmechanical strength) and high conductivity. The signal transmissionlines that conduct the recorded neural signal to an external electricalinterface can also be made from the well-tuned highly conductivematerials described in this invention. Thus, by combining a small volumeof nanostructured materials with large volumes of well-tuned material ofappropriate magnetic susceptibility, an optimum combination of highsignal-to-noise ratio, low negative immune response, low magneticsusceptibility and image artifacts and low eddy current heating can beachieved.

An example of the present subject matter can be configured as anelectrode array coating and can overcome some of the challenges thatcurrently prevent the use of MRI/fMRI and in vivo MR spectroscopy (MRS)for investigating the mechanisms underlying DBS treatment and forimprovement of treatment efficacy, for studying the relationship betweenthe BOLD signal and neural activity, and for studying the mechanismsunderlying additional treatments including spinal cord stimulation andvagus nerve stimulation.

Current commercial electrodes used in DBS are made fromplatinum-iridium. An example of the present subject matter includes anelectrode made from specially-created materials with tuned magneticsusceptibility and with additional use of nanostructured carbonnanotubes (CNTs) or other nanostructured materials of high surface area.While CNTs have been used for academic research, their benefits for MRIapplications have not been recognized even in academic research papers.Some have proposed use of CNTs for DBS electrodes from the point of viewof improving electrical charge collection and for better interfacingwith brain tissue cells. CNTs offer additional valuable benefits for MRIimaging which are being presented for the first time in this research.An example of the present subject matter includes materials withmagnetic susceptibility tuned to equal (or match) that of brain tissue.This type of tuned material will be obtained by using combinations ofparamagnetic and diamagnetic materials in the correct volume ratio andgeometry. The combinations of materials can be achieved by using alloysof the proposed individual material components, by using layer-by-layerdepositions of the individual materials in alternate thin film layers,or by using a composite network of conductive nanorods.

1) The magnetic susceptibility of the materials described in thisdocument is much closer to that of brain tissue than that of traditionalmetallic electrodes. Hence electrodes made of these materials createalmost no MRI image artifacts from their presence. This becomesespecially valuable at ultra-high magnetic fields where traditionalmetallic electrodes create image artifacts of such a magnitude as tomake MRI imaging unusable at the brain regions close to that of theelectrodes.

2) The locations of the electrodes including their tips can be preciselyimaged and identified by high-resolution structural MRI without imagedistortion. This can be helpful in deep brain stimulation (DBS) foroptimization of DBS electrode location and for studying the mechanismand efficacy of DBS treatment. This is also useful for studying therelationship between the BOLD signal and underlying co-located neuralelectrical activity.

3) CNT and other nanostructured electrode materials provide improvedadherence of tissue cells to the electrode and lower the chances ofinflammation or tissue scarring when used in long-term electrodeimplants. Furthermore, CNT and other nanostructured materials canpotentially reduce eddy currents which can lead to tissue heating (amajor safety concern for metal electrodes in MRI applications). Sincethe nanotubes/nanoflakes in the CNT electrodes are randomly distributedto disturb the eddy current flow and since CNT has lower metallicdegrees than metals, these electrodes can have weaker eddy currents thanmetallic electrodes under the same magnetic fields. An example of thepresent subject matter allows exploiting the desirable properties ofCNTs by combining CNT films in low volume with high volumes of otherwell-tuned materials with magnetic susceptibility matching that of braintissue.

Additionally, conductive polymer coatings can be used to improve thesurface roughness of such specially tuned MRI-compatible neuralrecording/stimulating probes. One such example includes a coating ofPoly(3,4-ethylenedioxythiophene), also known as PEDOT. Because somepolymers have a magnetic susceptibility that is close to that of tissue,a substantial thickness of conductive polymer material at the electroderecording/stimulating location can improve the electrochemical contactbetween the electrode and the tissue without introducing significantmagnetic field distortion in high field or clinical MRI.

It is also possible to use conductive nanorods to create a rough surfacefor the electrochemical recording/stimulating interface. Conductivenanorods of gold and aluminum can be used to create electrodes that havespecially tuned magnetic susceptibility to match brain tissue along withthe roughness that improves electrochemical contact. Furthermore, therandomly oriented structure of deposited nanorods can help to reducewith eddy currents during MRI, which contribute to electrode heating andpose a safety hazard. Therefore, conductive nanorod composites replicatethe advantages of CNT coatings, but can also be tuned for matching themagnetic susceptibility to brain tissue to eliminate image artifacts.

Simulation studies can be conducted on the influence of magneticsusceptibility on magnetic imaging artifacts. Such studies have useddiscrete numerical solutions of partial differential equationsdescribing magnetic scalar potential distribution in continuous2-dimensional volumes of composite materials. Simulation studies canprovide information on volume thresholds and susceptibility mismatchthresholds that lead to imaging artifacts. The simulation studies can beused to micro-fabricate an electrode with well-tuned susceptibilityproperties.

Simulation Method

To consider the effects of both the, volume magnetic susceptibility andgeometry of the electrodes during MRI, a 2D magnetic field simulator canbe implemented. Other have described a solver to calculate magneticfield distortions corresponding to an object of interest, where theobject is discretized and the discrete magnetic susceptibility of eachnode is defined. The solution can utilize the magnetic scalarpotentialΦ, which is defined per Equation 1, where H is the magneticfield strength.

H=−∇Φ  Equation 1

One problem entails calculating the unknown magnetic scalar potentialsat each node corresponding to the defined magnetic susceptibilitydistribution. An equation involving the magnetic susceptibility x andmagnetic scalar potential Φ is available. Specifically, for a magneticpermeability distribution μ_(r) (note that μ_(r)=x+1), the magneticscalar potential Φ is constrained per Equation 2, that is the divergenceof the product of the permeability and the gradient of the scalarpotential is zero.

∇·(μ_(r)∇Φ)=0   Equation 2

The simulation calculates the magnetic scalar potential corresponding toa defined magnetic volume susceptibility distribution. A direct solutionmethod is used rather than a convergent pseudo-time approach. ExpandingEquation 2 in two dimensions (x and z) results in Equation 3, where z isdefined to be aligned with the applied static magnetic field and x isorthogonal to z.

$\begin{matrix}{{{\frac{\partial\mu_{r}}{\partial x}\frac{\partial\Phi}{\partial x}} + {\mu_{r}\frac{\partial^{2}\Phi}{\partial x^{2}}} + {\frac{\partial\mu_{r}}{\partial z}\frac{\partial\Phi}{\partial z}} + {\mu_{r}\frac{\partial^{2}\Phi}{\partial z^{2}}}} = 0} & {{Equation}\mspace{14mu} 3}\end{matrix}$

Equation 3 becomes a linear system when applied on a uniform grid andapproximated by finite difference methods (see FIG. 1 for avisualization of the grid). For a node with a scalar potential Φ_(o)(node 5 in FIG. 1), the first and second partial derivatives of Φ withrespect to x and z can be approximated by the central difference method,leading to the form of Equation 4. The permeability of each node isdefined to create the object of interest, so μ_(r) is known and thespatial partial derivatives of μ_(r) can be approximated by finitedifference methods at each node on the grid. Therefore, μ_(r) and itsapproximate spatial derivatives are known for each node in the grid.

$\begin{matrix}{{{\frac{\partial\mu_{r}}{\partial x}\lbrack \frac{\Phi_{0 + {\Delta \; x}} - \Phi_{0 - {\Delta \; x}}}{2\Delta \; x} \rbrack} + {\mu_{r}\lbrack \frac{\Phi_{0 + {\Delta \; x}} + \Phi_{0 - {\Delta \; x}} - {2\Phi_{0}}}{\Delta \; x^{2}} \rbrack} + {\frac{\partial\mu_{r}}{\partial z}\lbrack \frac{\Phi_{0 + {\Delta \; z}} - \Phi_{0 - {\Delta \; z}}}{2\Delta \; z} \rbrack} + {\ldots \mspace{14mu} {\mu_{r}\lbrack \frac{\Phi_{0 + {\Delta \; z}} + \Phi_{0 - {\Delta \; z}} - {2\Phi_{0}}}{\Delta \; z^{2}} \rbrack}}} \approx 0} & {{Equation}\mspace{14mu} 4}\end{matrix}$

Equation 4 can be rearranged into the form of Equation 5, and used as aconstraint on the magnetic scalar potential at each interior node,specifically a linear combination of the magnetic scalar potentialsinvolving the central and four adjacent nodes. The partial spatialderivatives of μ_(r) in Equation 5 can be approximated by discretefinite difference methods, but the continuous derivative notation can beused so that the form of Equation 5 does not become unnecessarilycomplicated.

$\begin{matrix}{{{\Phi_{0}\lbrack {\frac{{- 2}\mu_{r}}{\Delta \; x^{2}} + \frac{{- 2}\mu_{r}}{\Delta \; z^{2}}} \rbrack} + {\Phi_{0 - {\Delta \; z}}\lbrack {\frac{\mu_{r}}{\Delta \; z^{2}} - \frac{{\partial\mu_{r}}\text{/}{\partial z}}{2\Delta \; z}} \rbrack} + {\Phi_{0 + {\Delta z}}\lbrack {\frac{\mu_{r}}{\Delta \; z^{2}} + \frac{{\partial\mu_{r}}\text{/}{\partial z}}{2\Delta \; z}} \rbrack} + {\ldots \mspace{14mu} {\Phi_{0 - {\Delta \; x}}\lbrack {\frac{\mu_{r}}{\Delta \; x^{2}} - \frac{{\partial\mu_{r}}\text{/}{\partial x}}{2\Delta \; x}} \rbrack}} + {\Phi_{0 + {\Delta \; x}}\lbrack {\frac{\mu_{r}}{\Delta \; x^{2}} + \frac{{\partial\mu_{r}}\text{/}{\partial x}}{2\Delta \; x}} \rbrack}} \approx 0} & {{Equation}\mspace{14mu} 5}\end{matrix}$

The bracketed scalar weights containing magnetic permeability and gridlengths in Equation 5 can be computed for each node in the defined gridcorresponding to the object of interest. Vectors Φ and u and matrices Aand B are defined to satisfy the constraints for all the interior nodesin the model as described below.

A {right arrow over (Φ)}+B {right arrow over (u)}={right arrow over(0)}  Equation 6

The vector Φ contains the unknown magnetic scalar potential at eachinterior node in the grid, and the vector u contains boundary conditionson the magnetic scalar potential at each boundary node. The boundaryconditions can be created by placing the boundary nodes far away fromthe object of interest and assuming the magnetic scalar potential at theboundary is unaffected by the presence of the object. The scalarpotential at the boundary can be computed through integration ofEquation 1 for a particular applied field H.

Matrices A and B are systematically defined so that Equation 5 iswritten for each interior node of unknown magnetic scalar potential. Thenumber of rows in A and B are equal to the number of interior nodes inthe grid, that is the number of unknown magnetic scalar potentials; A isa square matrix and the number of columns in B corresponds to the numberof boundary nodes minus four, as the corners of the boundaries are notused by the central difference approximations on any interior nodes. Thebracketed scalar weights for each interior node are assigned to the rowcorresponding to that node and the appropriate column in A or B suchthat the weights for each node are multiplied by the appropriate scalarpotential in either Φ or u. The result is a system of linear equationscontaining Equation 5 for every interior node in the grid. The system isrepresented in Equation 6 as the sum of two matrix-vector products.

To discretize an object of arbitrary curvatures in a large enoughfield-of-view such that the boundary magnetic scalar potentials areunaffected by the object may require several hundred nodes in eachdirection. In such cases, A and B are sparse matrices, e.g. for a gridof 512×512 nodes the number of columns in A and rows in A and B is260,1.00, and the number of columns in B is 2,040; but the number ofnonzero entries in each row of an augmented matrix [AIB] is only five,corresponding to the five magnetic scalar potentials in Equation 5.Rather than solve Equation 6 for the unknown magnetic scalar potentialsin Φ by inversion of the sparse matrix A, the system can be re-writtenin the form of Equation 7.

$\begin{matrix}{{\lbrack A \middle| B \rbrack \lbrack \frac{\overset{arrow}{\Phi}}{\overset{arrow}{u}} \rbrack} = \overset{arrow}{0}} & {{Equation}\mspace{14mu} 7}\end{matrix}$

The solution is found by numerically computing the reduced row echelonform of the augmented matrix [AIB] which, by definition, has the form ofthe matrix in Equation 8, where I is the identity matrix the size of A.

$\begin{matrix}{{\lbrack I \middle| K \rbrack \lbrack \frac{\overset{arrow}{\Phi}}{\overset{arrow}{u}} \rbrack} = \overset{arrow}{0}} & {{Equation}\mspace{14mu} 8}\end{matrix}$

The unknown magnetic scalar potentials can be calculated per Equation 9.

{right arrow over (Φ)}=−K{right arrow over (u)}  Equation 9

The magnetic induction or magnetic flux density B is calculated from thecomputed magnetic scalar potentials with finite differenceapproximations of Equation 10, which only applies for non-ferrousobjects such that B and H are linearly related.

B=μ _(o)μrH=μ_(o)μ_(r)(−∇Φ)   Equation 10

The approach described in Equations 1-10 compute the magnetic fluxdensity, or B-field, around an object of arbitrary volume magneticsusceptibility distribution in an applied magnetic field of strength H.

The distortion of the B-field by an object can be defined as thedifference between the numerically calculated B-field and the analyticalbackground B-field in the absence of the object, normalized by thebackground B-field, and reported in ppm. The root-mean-square (RMS) ofthe distorted B-field can be used to compare the severity of fielddistortion across the field-of-view between simulations.

Simulation Validation and Limitations

The distortion of the static B-field by a hollow cylinder of water inair (in unit of PPM) can be mapped, and error maps between filterednumerical and analytical solutions can indicate that the numericalsolution provides an accurate estimate of magnetic field distortion.

The solver has the following limitations:

1) The solver is 2D, so cross sections simulated are assumed infinitelylong; the approach can be applied in 3D at the expense of computationtime.

2) There is a spatial resolution vs. field-of-view (FOV) tradeoff thatlimits simulation of fine features on large length scales.

Simulation of Tunable Electrode Susceptibility

The following portion provides some simulation results regarding atunable susceptibility concept. The simulation scheme is also described.

To reduce image artifacts in magnetic resonance imaging, it can behelpful to match the electrode susceptibility to that of the surroundingtissue or water. A close match in magnetic susceptibility reducesmagnetic field distortions and consequently reduces image artifacts.

The static magnetic field distortions around an individual neuralelectrode signal line of varying material composition can be simulated.The different materials have different magnetic susceptibility values.In at least one example, the signal lines are 1.1 microns thick and 3microns wide, which is a reasonable size for microfabricated MRIcompatible neural electrode signal lines. Two orientations areconsidered (elongated side of signal line cross section either parallelor perpendicular to static field direction). The static field is alignedwith axis z. The simulation is 2D so the signal lines are assumedinfinitely long.

In some examples, only signal lines are simulated, because they arecomposed of metals that are not well-matched with the tissuesusceptibility. Various polymer materials have a good susceptibilitymatch to tissue that can act as substrates for the neural probes. Thesusceptibility map plots can have the same colormap scaling, and thefield distortion maps can have the same colormap scaling for comparisonpurposes.

First, a copper signal line is simulated. For copper, the magneticsusceptibility difference from tissue (Δ_(x)) is less than 1 ppm. Thecopper wire cross section in the water (similar to the tissue)background cannot be distinguished with the scaling used, and the fielddistortions are extremely faint. Copper would be an excellent materialchoice in MR-compatible neural probes based on its magneticsusceptibility; however, copper is cytotoxic and will damage the neuraltissue which it comes into contact. One example of the present subjectmatter includes an electrode of biocompatible material havingsusceptibility tuning with similar or better magnetic susceptibilityvalue compared to copper that will not damage neural tissues.

Other conductors, such as gold and aluminum, have magneticsusceptibility values significantly different than tissue and createfield distortions. Aluminum is paramagnetic (positive susceptibility),while gold is diamagnetic (negative susceptibility). Therefore, acombination of these materials allows tuning the magnetic susceptibilityto be equivalent to the particular value of the susceptibility of water.When mapping susceptibility and field distortion for an aluminum-basedelectrode or a gold-based electrode, field distortions are apparentaround both electrodes, since they are not well matched in magneticsusceptibility to the surrounding tissue.

The percentage of gold in a gold-aluminum composite sufficient toachieve the effective particular susceptibility can be found by thefollowing formula:

Δx _(au)(%_(au))+Δx _(al)(1-%_(au))=0

Substituting values reveals that, in theory, a gold-aluminum compositemade of approximately 54% gold will have the same volume-averagedsusceptibility value as water.

Two composites can be simulated. First, alternating layers of 100 nmgold and aluminum can be stacked with six layers of gold sandwichingfive layers of aluminum (6/11=0.545). Such a composite structure can befabricated using physical vapor deposition techniques (such asevaporation or sputtering), which are available in a nanofabricationfacility. The results can reveal that field distortions still existwithin the signal line, but the distortions outside the signal line arereduced, especially in comparison to pure gold or pure aluminum signallines.

Additionally, a “diffused” composite of 50% gold and 50% aluminum can besimulated. Similar results can be obtained as the layer-wise stackingcomposite. In this example, the field distortions still exist within thesignal line but distortions outside the signal line are significantlyreduced compared to the case of pure aluminum or pure gold.

In viewing field distortion results for a diffused metal electrodecomposed of gold and aluminum, the total root-mean-square (RMS) of themagnetic field distortion across the simulated field can be shown. Theseresults can be compared with those of copper. Copper provides a goodoption for reducing distortions over the whole field (both in tissue andin the signal line itself). The layering approach and diffusion approachfor composite gold-aluminum materials reduces RMS distortion across thewhole field but not to the same level as the copper signal line. This isbecause distortions still exist within the signal line for the compositematerials. However, this should not result in an issue for MRIapplication since the electrode itself is not detected by MRI.

Consider next the distortions only within the tissue (i.e. masking outthe contribution of distortions within the signal line cross-section).The composite materials approach the performance of the copper signalline. Even using a relatively coarse resolution for these simulations(e.g., 100 nm node spacing and only 128 nodes in each direction)paramagnetic and diamagnetic materials can be combined to significantlyreduce the magnetic field distortions in the surrounding tissue whencompared to using a pure paramagnetic or pure diamagnetic signal line. Alayer-wise composite structure can be fabricated with significantlythinner layers and alloys can be fabricated with better homogeneity thanthose simulated. The described simulations were limited by computationtime constraints. Such improvements may further reduce field distortionsin the tissue and perhaps even within the signal line.

One example of the present subject matter allows tuning of thesusceptibility of a composite material to match that of brain tissue,and thus, provides better performance than a copper signal line. Thebiocompatibility of such composites can be evaluated by comparison tocytotoxic copper and materials such as platinum or gold that are knownto be biocompatible.

In Vivo Example—CNTs

A CNT electrode and a commercial linear probe array can be implantedbilaterally into the somatosensory cortex of a male Sprague-Dawley ratunder isoflurane anesthesia. Anesthesia can be induced with 5%isoflurane, and then maintained between 1.5 and 3% isoflurane for theduration of the surgery and experiment. A (bilateral) craniotomy can beperformed over the primary somatosensory forelimb cortex (S1FL) in eachhemisphere, and electrodes can be implanted with a stereotaxic system.Neural activity can be simultaneously recorded from the probes under1.6% isoflurane at 30 kHz, using a Cerebus data acquisition system(Blackrock Microsystems, Salt Lake City, Utah). An ex vivo noise floorcan be recorded at the end of the experiment to compare the SNR of theprobes. Noise filtering (60 Hz) can be applied during post processing inMATLAB, and signals can be low-pass filtered to isolate local fieldpotentials (LFPs <500 Hz).

Additionally, 2-slice MR-imaging can be performed in an anesthetized ratimplanted with a single CNT electrode in the left somatosensory cortex.Again, anesthesia can be induced with 5% isoflurane, and then maintainedbetween 1.5 and 3% isoflurane for the duration of the surgery andexperiment. The animal can be intubated and catheterized via the femoralartery prior to being placed in an MR-compatible cradle, and securedwith bite and ear bars. A small craniotomy can be performed over theprimary somatosensory forelimb cortex in the left hemisphere. A plasticanchor can be attached to the contralateral skull for electrodestabilization. The electrode can be inserted into the cortex using astereotaxic system, and dental cement applied to secure the electrodeand close the craniotomy. The animal's body temperature can bemaintained at 37° C. with a heated water pad. Artificial breathingcontrolled by a ventilation machine can be adjusted to maintain normalblood gases. At the end of the study, a bolus of potassium chloride(KCl) can be injected into a venous line to induce a heart attack.Imaging can be performed on a 9.4T/31 cm horizontal bore magnet with aVnmrJ console (Agilent, Santa Clara, Calif.) and a custom RF coil.Multi-slice gradient echo (GEMS) and fast spin echo (FSEMS) sequencescan be performed to acquire whole brain anatomical images in sagittal,axial, and coronal orientations with a resolution of 156.3 μm or 78.1 μm(FOV 40×40 mm, slice thickness 0.5 or 1 mm, 256×256 of 512×512 imagematrix size). Functional imaging can be acquired using T2*-weightedsingle shot echo planar imaging sensitive to the BOLD contrast (gradientecho EH, TR 612 ms, TE 17 ms, FOV 40×40 mm, 64×64 voxels, slicethickness 1 mm, 1-3 slices).

MRI images can be loaded into MATLAB with the AEDES toolbox. Networkconnectivity maps can be calculated using a seed based correlationanalysis and overlaid on slice matched anatomical images with athreshold of p <0.05 and correlation coefficient lccl >0.5.

In vivo experimentation in an anesthetized rat can reveal that oneexample of a CNT neural electrode can achieve higher SNR than commercialelectrodes. This SNR improvement may be related to the highelectrochemical surface area of the CNT electrode. Additionally, bothstructural and functional MR images can be obtained around an implantedCNT electrode in vivo at a field strength of 9.4T with low artifacts asshown in FIG. 10D. The ability to obtain functional images around animplanted neural electrode with high SNR in neural signals is useful forunderstanding the brain, since simultaneous electrophysiology andfunctional hemodynamic/metabolic data could be combined.

Nanorod Composites and Eddy Current Reduction

An example of the present subject matter is configured for fabricationneural electrodes with tunable magnetic susceptibility. The magneticsusceptibility of the electrodes can be matched to that of brain tissueby using a combination of paramagnetic and diamagnetic materials in aselected proportion to obtain a combined equivalent susceptibilitymatched with that of the brain tissue.

The following provides an example of a particular embodiment of thepresent subject matter.

In one embodiment, nanorods of gold and aluminum (diamagnetic andparamagnetic respectively) can be used to form the conductiveelectrodes. By using randomly oriented networks of nanorods instead of acontinuous layer of material, eddy currents in the electrodes caused bythe changing magnetic fields in the MRI machine are reduced. Thus, anelectrode of the present subject matter will both provide low MRI imageartifacts and also low heating of tissue (due to low eddy currents). Inat least one example, aluminum (Al) nanorods in water can be combinedwith gold (Au) nanorods in water. A combination of Au and Al, can beused to tune magnetic susceptibility to equal or match (or substantiallyequalch or mat) that of brain tissue.

One example includes an electrode having Au and Al nanorods in arandomly oriented multi-layered network. In one example, each signalline and electrode of a neural probe can be fabricated of Al and Aunanorods mixed in the selected proportion (for example, about 46% toabout 54% by volume). The nanorods can form conductive networks that arefabricated to form electrodes and signal lines. Fabrication can includeetching or fabricating using lift-off techniques.

In some examples, a randomly oriented network of nanorods can beadvantageous in that eddy currents induced in the loops in the networktend to cancel each other's effects. Eddy currents are expected to hevery low in a conductive network compared to a continuous electrodesurface. The nanorod network in the presence of a varying externalmagnetic field can result in a magnetic field in the opposite directionof the applied magnetic field, due to the induced current. In someexamples, currents in each nanorod can cancel each other in every sideof the loops. In some examples, the only remaining eddy currents in thenetwork of nanorods are current loops induced within each nanorod. Theseare expected to be very low because each nanorod is very thin (e.g.,tens of nanometers) and has high individual resistance due to very lowcross-section area.

Further Examples

FIG. 2 illustrates an embodiment of an electrode array 200, for example,a neural recording electrode array. In the example shown, the electrodearray 200 includes a substrate 202 having a plurality of electrical pads204, each of which is coupled to a separate electrode 206 positioned inthe penetrating substrate tip 208. Each separate electrode 206 iscoupled to an electrical pad 204, in a one-to-one relation, by a signalline 210. Each signal line 210 is disposed on the substrate 202 andbeneath a layer of insulation 214. In at least one example, eachelectrode 206 is a recording electrode. In some examples, the electrodearray 200 also includes a reference electrode 212. In other examples,the electrodes 200 could be a stimulating electrode, or a recording andstimulating electrode. In some examples, one or more of the electrodes206 can be stimulating electrodes. In at least one example, theelectrical pads 204 can be coupled to another device to facilitaterecording or stimulating.

The figure indicates a section taken at cut line 222-222 and a detailview at 224 near the tip of the electrode array 200. Various examples ofsection view 222 and detail view 224 are described in subsequentfigures. Note that certain details in the figures of this document arenot necessarily depicted in scale but are drawn for clarity inillustrating concepts and claims. For example, the signal lines 210 mayappear nearly equal in dimension to the insulation 214 however, this isnot necessarily the case.

FIG. 3A illustrates an example 300 of section view 222, and FIGS. 3B,3C, 3D, and 3E illustrate examples of detail view 224. In the example300 shown in FIG. 3A, the section view taken at 222-222 (with respect toFIG. 2) illustrates that the signal lines 210 are disposed on thesubstrate 202 and electrically isolated by the layer of insulation 214.In the illustrated example, the electrodes and signal lines 210 arefabricated of alternating layers of diamagnetic materials 302 andparamagnetic materials 304 balanced in a particular volumetric ratiosuch that the effective bulk magnetic susceptibility is tunable to thatof neural tissue. In at least one example, the signal lines 210 caninclude alternating layers of gold (diamagnetic) and aluminum(paramagnetic). The thickness of each individual layer can range fromtens to hundreds of nm. In at least one example each layer has athickness of between 1 and 1000 nm.

As shown in FIG. 3B, a buried signal line 210 can terminate at anexposed electrode 206. The electrode 206 exposed to the tissue in FIG.3B can be of the diamagnetic material 302 or can be of the paramagneticmaterial 304. In at least one example, the electrode 206 can befabricated of alternating layers of diamagnetic material 302 andparamagnetic material 304. The exposed electrode 206 can be configuredfor recording a physiological parameter.

As shown in FIG. 3C the buried signal line 210 can terminate at anelectrode 206, as described with reference to FIG. 3B that can furtherinclude a thin layer of carbon nanotubes (CNTs) 310 at the exposedelectrode 206. The CNTs 310 increase the electrochemical surface areafor interfacing with the neural tissue, thus increasing thesignal-to-noise ratio (SNR). In one example, the thickness of theunderlying alternating layers of diamagnetic 302 and paramagnetic 304material is a total of 1 micron and the CNT 310 has a total thickness of50 nm. In at least one example, the layer of CNT 310 can have athickness of approximately 10-200 nm. In at least one example, the CNTlayer 310 is relatively thin. In at least one example, the CNT layer 310is thin because a carbon nanotube does not necessarily possess magneticsusceptibility close to that of neural tissue.

As shown in FIG. 3D, a layer of electrically conductive polymer 320 isdeposited onto the exposed electrode 206 described with reference toFIG. 3B. The conductive polymer 320 has a rough surface and increasesthe electrochemical surface area, thus increasing the SNR. Becausepolymers generally have magnetic susceptibility close to neural tissue,the layer does not necessarily need to be very thin. An example of aconductive polymer 320 includes Poly(3,4-ethylenedioxythiophene),sometimes referred to as PEDOT.

As shown in FIG. 3E, a thin layer of biocompatible conductive material330 can be positioned over the exposed electrode 206 described withreference to FIG. 3B to improve the biocompatibility of the electrodes206. Such a biocompatible conductive layer 330 may be advantageousdepending on the composition of the underlying alternating layers ofdiamagnetic 302 and paramagnetic 304 material. The biocompatibleconductive layer 330 can be fabricated by deposition, or by a removalprocess or by a patterning technique (lithography). In at least oneexample, the biocompatible conductive material 330 can comprise gold(Au).

FIG. 4A illustrates an example 400 of section view 222, and FIGS. 4B,4C, 4D, and 4E illustrate examples of detail view 224. In the example400, the signal lines 210 are fabricated of a metallic alloy 402 made bydiffusion of diamagnetic and paramagnetic materials balanced in thecorrect volumetric ratio such that the effective bulk magneticsusceptibility is tunable to that of neural tissue. An exampleembodiment involves diffusion of gold (diamagnetic) and aluminum(paramagnetic). The alloy can be made by depositing very thin (forexample, 5 nm or less than about 5 nm) alternating layers of diamagneticand paramagnetic materials by evaporation followed by heating to promotediffusion. In one example, the diamagnetic and paramagnetic materialscan be co-deposited by sputtering.

As shown in FIG. 4B, a buried signal line 210 can terminate at anexposed electrode 206. The electrode 206 exposed to the tissue can be ametallic alloy 402 made by diffusion of diamagnetic and paramagneticmaterials.

As shown in FIG. 4C the buried signal line 210 can terminate at anelectrode 206, as described with reference to FIG. 4B, that can furtherinclude a thin layer of carbon nanotubes (CNTs) 410 at the exposedelectrode 206. The CNTs 410 increase the electrochemical surface areafor interfacing with the neural tissue, thus increasing thesignal-to-noise ratio (SNR). In at least one example, the totalthickness of the underlying alloy 402 can be about 1 micron or less. Inat least one example, the total thickness of the underlying alloy 402can be about 1 micron. In at least one example, the layer of CNT 410 canhave a thickness of approximately 10-200 nm. In at least one example,the CNT 410 thickness can be about 50 nm or less. In at least oneexample, the CNT 410 thickness can be about 50 nm. In some embodiments,the CNT layer 410 is thin because CNTs do not necessarily possessmagnetic susceptibility close to that of neural tissue.

As shown in FIG. 4D, a layer of electrically conductive polymer 420 isdeposited onto the exposed electrode 206 described with reference toFIG. 4B. The conductive polymer 420 has a rough surface and increasesthe electrochemical surface area, thus increasing the SNR. Becausepolymers generally have magnetic susceptibility close to neural tissue,the layer 420 does not necessarily need to be very thin. An example of aconductive polymer 420 includes Poly(3,4-ethylenedioxythiophene),sometimes referred to as PEDOT.

As shown in FIG. 4E, a thin layer of biocompatible conductive material430 can be positioned over the exposed electrode 206 described withreference to FIG. 4B to improve the biocompatibility of the electrodes206. Such a biocompatible conductive layer 430 may be advantageousdepending on the composition of the underlying alloy. The biocompatibleconductive layer 430 can be fabricated by deposition, or by a removalprocess, or by a patterning technique (lithography). In at least oneexample, the biocompatible conductive material 430 can comprise gold(Au).

FIG. 5A illustrates an example 500 of section view 222 and FIGS. 5B, 5C,5D, and 5E illustrate examples of detail view 224. In the example 500shown in FIG. 5A, the section view taken at 222-222 (with respect toFIG. 2) illustrates that the signal lines 210 are disposed on thesubstrate 202 and electrically isolated by the layer of insulation 214.In the illustrated example, the electrodes and signal lines 210 arefabricated of randomly oriented conductive nanorods 502 of diamagneticand paramagnetic materials balanced in the correct volumetric ratio suchthat the effective bulk magnetic susceptibility is tunable to that ofneural tissue. An example embodiment involves nanorods 502 of gold(diamagnetic) and aluminum (paramagnetic). The randomly orientednanorods 502 can reduces the eddy currents caused by time-varyingmagnetic fields in MRI because induced currents will be in randomdirections and therefore opposing currents will cancel out. In addition,the randomly oriented nanorods 502 can increase surface roughness (andelectrochemical surface area) at the exposed electrodes 206 to improveSNR. In at least one example, the randomly oriented conductive nanorods502 can include a network of randomly oriented conductive materialsselected from the group consisting of: conductive nanorods,nanomaterials, and micro-structured conductive materials.

As shown in FIG. 5B, a buried signal line 210 can terminate at anexposed electrode 206. The electrode 206 exposed to the tissue in FIG.5B can include randomly oriented conductive nanorods 502 of diamagneticand paramagnetic materials.

As shown in FIG. 5C the buried signal line 210 can terminate at anelectrode 206, as described with reference to FIG. 5B, that can furtherinclude a thin layer of carbon nanotubes (CNTs) 510 at the exposedelectrode 206. The CNTs 510 increase the electrochemical surface areafor interfacing with the neural tissue, thus increasing thesignal-to-noise ratio (SNR). In one example, the thickness of theunderlying nanorod composite 502 can be about 1 micron or less and theCNT 510 can have a total thickness of about 50 nm or less. In at leastone example, the thickness of the underlying nanorod composite 502 isabout 1 micron. In at least one example, the layer of CNT 510 can have athickness of approximately 10-200 nm. In at least one example, the CNT510 has a thickness of about 50 nm. In at least one example, the CNT 510is configured as a relatively thin layer. A carbon nanotube does notnecessarily possess magnetic susceptibility close to that of neuraltissue

As shown in FIG. 5D, a layer of electrically conductive polymer 520 isdeposited onto the exposed electrode 206 described with reference toFIG. 5B. The conductive polymer 520 has a rough surface and increasesthe electrochemical surface area, thus increasing the SNR. Becausepolymers generally have magnetic susceptibility close to neural tissue,the polymer layer 520 does not necessarily need to be very thin. Anexample of a conductive polymer 520 includesPoly(3,4-ethylenedioxythiophene), sometimes referred to as PEDOT. Asshown in FIG. 5E, a thin layer of biocompatible conductive material 530can be positioned over the exposed electrode 206 described withreference to FIG. 513 to improve the biocompatibility of the electrodes206. Such a biocompatible conductive layer 530 may be advantageousdepending on the composition of the randomly oriented conductivenanorods 502. The biocompatible layer 530 can be fabricated bydeposition, or by a removal process, or by a patterning technique(lithography). In at least one example, the biocompatible conductivematerial 530 can comprise gold (Au).

FIG. 6 is a flowchart illustrating an example method 600 of fabricatinga neural recording/stimulating electrode, in accordance with at leastone embodiment. At block 602, a substrate is provided. In at least oneexample, the substrate can be a polyimide substrate.

At block 604, at least one signal line is formed on the substrate. In atleast one example, the at least one signal line can have a diamagneticmaterial and paramagnetic material in a ratio determined by theproperties of physiological tissue. In at least one example, forming thesignal line includes selecting a volumetric ratio between at least twomaterials. In at least one example, selecting the volumetric ratioincludes selecting, based on a magnetic susceptibility of the signalline. In some examples, the volumetric ratio is selected tosubstantially match the magnetic susceptibility with that of thephysiological tissue. In at least one example, the signal line is formedusing gold. In at least one example, the signal line is formed usingaluminum. In some examples, the signal line is formed using layers ofdiamagnetic material and paramagnetic material with respect to aphysiological tissue. In some examples, the layers can have a thicknessof between 1 and 1000 nm. In at least one example, the signal line isfabricated by diffusion. In at least one example, the signal line isformed by depositing layers. In some examples, the signal line is formedincludes evaporating and heating. In some examples, forming the signalline includes co-depositing the diamagnetic material and theparamagnetic material. In at least one example, forming the signal lineincludes forming a network of randomly oriented conductivenanorods/nanomaterials. In some examples, forming the signal lineincludes using a common fabrication technique.

At block 606, at least one electrode is formed, and each electrode iscoupled to a signal line generally in a one-to-one relationship. In someexamples, the at least one electrode can have a diamagnetic material andparamagnetic material in a ratio determined by the properties ofphysiological tissue. In at least one example, block 606 furtherincludes selecting the ratio to substantially match the magneticsusceptibility with that of the physiological tissue. In at least oneexample, forming the electrode includes selecting a volumetric ratiobetween at least two materials. In at least one example, the volumetricratio is selected based on a magnetic susceptibility of the electrode.In some examples, the volumetric ratio is selected to substantiallymatch the magnetic susceptibility with that of the physiological tissue.In at least one example, the electrode is formed using gold. In at leastone example, the electrode is formed using aluminum. In some examples,the electrode is formed using layers of diamagnetic material andparamagnetic material with respect to a physiological tissue. In someexamples, the layers can have a thickness of between 1 and 1000 nm. Inat least one example, the electrode is fabricated by diffusion. In atleast one example, the electrode is formed by depositing layers. In someexamples, the electrode is formed includes evaporating and heating. Insome examples, forming the electrode includes co-depositing thediamagnetic material and the paramagnetic material. In at least oneexample, forming the electrode includes forming a network of randomlyoriented conductive nanorods/nanomaterials. In some examples, formingthe electrode includes using a common fabrication technique.

In at least one example, the electrode is formed with a layer of carbonnanotubes at an exposed electrode surface. In some examples, the layerof carbon nanotubes can be formed to have a thickness of betweenapproximately 10 and 200 nm. In some examples, the electrode can beformed with a layer of electrically conductive polymer at an exposedelectrode surface, for example PEDOT. In at least one example, theelectrode can be formed with a layer of biocompatible conductivematerial at an exposed electrode surface, for example gold. In at leastone example, the electrodes are formed so as to provide a variety ofMRI-compatible and biocompatible electrodes with particularsusceptibility which matches the tissue susceptibility for neuralrecording and brain stimulation with minimal MRI susceptibilityartifacts and tissue heating safety concern. In at least one example,the electrodes are applicable for other types of tissues and organsbesides the brain. In some examples, the ratio of diamagnetic andparamagnetic material is determined by the properties of thephysiological tissue. Generally, the properties of diamagnetic andparamagnetic are values relative to that of the tissue.

At block 608, insulation is selectively applied to the signal lines. Inat least one example, the insulation is applied to electrically isolatethe signal lines. In at least one example, the signal line is covered bythe insulation layer.

The above description includes references to the accompanying drawings,which form a part of the detailed description. The drawings show, by wayof illustration, specific embodiments in which the invention can bepracticed. These embodiments are also referred to herein as “examples.”Such examples can include elements in addition to those shown ordescribed. However, the present inventors also contemplate examples inwhich only those elements shown or described are provided. Moreover, thepresent inventors also contemplate examples using any combination orpermutation of those elements shown or described (or one or more aspectsthereof), either with respect to a particular example (or one or moreaspects thereof), or with respect to other examples (or one or moreaspects thereof) shown or described herein.

In the event of inconsistent usages between this document and anydocuments so incorporated by reference, the usage in this documentcontrols.

In this document, the terms “a” or “an” are used, as is common in patentdocuments, to include one or more than one, independent of any otherinstances or usages of “at least one” or “one or more.” In thisdocument, the term “or” is used to refer to a nonexclusive or, such that“A or B” includes “A but not B,” “B but not A,” and “A and B,” unlessotherwise indicated. In this document, the terms “including” and “inwhich” are used as the plain-English equivalents of the respective terms“comprising” and “wherein.” Also, in the following claims, the terms“including” and “comprising” are open-ended, that is, a system, device,article, composition, formulation, or process that includes elements inaddition to those listed after such a term in a claim are still deemedto fall within the scope of that claim. Moreover, in the followingclaims, the terms “first,” “second,” and “third,” etc. are used merelyas labels, and are not intended to impose numerical requirements ontheir objects.

Geometric terms, such as “parallel”, “perpendicular”, “round”, or“square”, are not intended to require absolute mathematical precision,unless the context indicates otherwise. Instead, such geometric termsallow for variations due to manufacturing or equivalent functions. Forexample, if an element is described as “round” or “generally round,” acomponent that is not precisely circular (e.g., one that is slightlyoblong or is a many-sided polygon) is still encompassed by thisdescription.

In at least one example, the term substantially means to a great orsignificant extent, nearly. In some examples, the term substantially maymean within plus or minus 10 percent.

Method examples described herein can be machine or computer-implementedat least in part. Some examples can include a computer-readable mediumor machine-readable medium encoded with instructions operable toconfigure an electronic device to perform methods as described in theabove examples. An implementation of such methods can include code, suchas microcode, assembly language code, a higher-level language code, orthe like. Such code can include computer readable instructions forperforming various methods. The code may form portions of computerprogram products. Further, in an example, the code can be tangiblystored on one or more volatile, non-transitory, or non-volatile tangiblecomputer-readable media, such as during execution or at other times.Examples of these tangible computer-readable media can include, but arenot limited to, hard disks, removable magnetic disks, removable opticaldisks (e.g., compact disks and digital video disks), magnetic cassettes,memory cards or sticks, random access memories (RAMs), read onlymemories (ROMs), and the like.

The above description is intended to be illustrative, and notrestrictive. For example, the above-described examples (or one or moreaspects thereof) may be used in combination with each other. Otherembodiments can be used, such as by one of ordinary skill in the artupon reviewing the above description. The Abstract is provided to allowthe reader to quickly ascertain the nature of the technical disclosure.It is submitted with the understanding that it will not be used tointerpret or limit the scope or meaning of the claims. Also, in theabove Detailed Description, various features may be grouped together tostreamline the disclosure. This should not be interpreted as intendingthat an unclaimed disclosed feature is essential to any claim. Rather,inventive subject matter may lie in less than all features of adisclosed embodiment. Thus, the following claims are hereby incorporatedinto the Detailed Description as examples or embodiments, with eachclaim standing on its own as a separate embodiment, and it iscontemplated that such embodiments can be combined with each other invarious combinations or permutations. The scope of the invention shouldbe determined with reference to the appended claims, along with the fullscope of equivalents to which such claims are entitled.

What is claimed is:
 1. A device comprising: a substrate having asurface; a signal line coupled to the substrate and covered by aninsulation layer; an electrical pad coupled to the signal line; and anelectrode coupled to the signal line; wherein at least one of theelectrode or the signal line includes a diamagnetic material and aparamagnetic material, wherein diamagnetic and paramagnetic are relativeto a physiological tissue, wherein a ratio of the diamagnetic materialand the paramagnetic material is selected based on the physiologicalsusceptibility property of the tissue.
 2. The device of claim 1, whereinthe physiological tissue is a neural or spinal tissue.
 3. The device ofclaim 1, wherein the physiological tissue is a or muscular tissue. 4.The device of claim 1, where the electrode is a recording electrode orstimulating electrode.
 5. A fabrication method comprising: providing asubstrate; forming a signal line on the substrate; forming an electrode,such that the electrode is coupled to the signal line, wherein at leastone of the electrode or signal line includes diamagnetic material andparamagnetic material relative to a physiological tissue in a ratiodetermined by the properties of the physiological tissue; andselectively applying insulation to the signal lines.
 6. The method ofclaim 5, wherein the ratio is a volumetric ratio.
 7. The method of claim5, further comprising: selecting the ratio to substantially match themagnetic susceptibility with that of the physiological tissue.
 8. Themethod of claim 5, wherein forming includes depositing layers of thediamagnetic and paramagnetic materials.
 9. The method of claim 5,wherein forming includes forming layers of diamagnetic material andparamagnetic material to substantially match the susceptibility propertyof the physiological tissue.
 10. The method of claim 5, wherein formingincludes diffusion of the paramagnetic and diamagnetic materials tosubstantially match the susceptibility property of the physiologicaltissue.
 11. The method of claim 5, wherein forming includes evaporatingand heating.
 12. The method of claim 5, wherein forming includesco-depositing the diamagnetic material and the paramagnetic material.13. The method of claim 5, wherein forming includes forming theelectrode or signal line to include a network of randomly orientedconductive materials selected from the group consisting of: conductivenanorods, nanomaterials, and micro-structured conductive materials. 14.The method of claim 5, further comprising: forming a variety ofMRI-compatible and biocompatible electrodes with particularsusceptibility that substantially matches the tissue susceptibility forneural recording and brain stimulation with minimal MRI susceptibilityartifacts or reduced eddy current and tissue heating.
 15. A devicecomprising: a substrate; a signal line coupled to the substrate; aninsulation layer covering the signal line; an electrical pad coupled tothe signal line; and an electrode coupled to the signal line, whereinthe electrode or signal line includes a network of randomly orientedconductive materials configured to reduce eddy current generation in aMRI system.
 16. The device of claim 15, wherein the electrode and signalline are fabricated of a material having a susceptibility propertycorresponding to a physiological tissue.
 17. The device of claim 15,wherein the electrode includes a layer of carbon nanotubes at an exposedsurface.
 18. The device of claim 15, wherein the electrode includes alayer of electrically conductive polymer at an exposed surface.
 19. Thedevice of claim 15, wherein the electrode includes a layer ofbiocompatible conductive material at an exposed surface.
 20. The deviceof claim 15, wherein the substrate has a magnetic susceptibility thatsubstantially matches that of the physiological tissue.